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GOVERNANCE
AS LEARNING: THE CHALLENGE OF DEMOCRACY"
TOM
BENTLEY
While Geoff Mulgan makes a strong case that learning has become central
to effective governance, Tom Bentley registers a missing dimension
in his argument: democracy itself. Learning is not just openness to
international experience among policy-makers, or a better chain of
command. It is a process that entails deep accountability, transparency,
network-based cultures of information at every level one that
recasts relationships between governments and people.
Read Anthony Barnetts introduction to the Mulgan /Bentley exchange,
charting the shift in governance under New Labours Third Way
from we know best to we learn best.
An Australian policy-maker who tracks policy-making on several continents
recently told me that the Strategy Unit in the UK Cabinet Office produces
the best government thinking in the world. Geoff Mulgans
essay does its best to justify this encomium with an overview that
fuses an independently-crafted intellectual panorama with an imaginative
and balanced approach to the rigours of policy formation inside government.
Mulgans brief was to address the changing nature of policy-learning
and international comparison at the centre. But his argument
that governments which learn and adapt best serve their citizens most
effectively is limited in two respects. For governance to work
well in the 21st century, policy has to help change whole, complex,
social and organisational systems. To do this, the relationship between
governments and people needs to change in two other closely related
ways.
Governments and people: change and constraint
The first challenge is implementation, where absorbing and acting
on the best of what can be learned from elsewhere requires a different
chain running from policy decision to administrative outcome and back
again. In Britain, the model of governance inherited from the 19th
century embodies a formal distinction between policy,
a set of objectives set by elected ministers, and its translation
into practice by a neutral, efficient, permanent civil service. This
assumes that political and administrative decision-making are structurally
separated. Governance as learning collapses this distinction,
which in reality is already a hazy one.
The second, more important, challenge is democracy. The institutional
design of parliamentary democracies also assumes that policy goals
and methods are legitimated through a separation of powers and processes.
The actions of governments are accountable to elected representatives
in parliaments. Parliaments and governments are formed through party-based
electoral competition, who organise their proposed policies into manifestos.
Elected governments undertake consultation processes in
order to test and refine their proposals with the public and civil
society.
But governance as learning implies a more direct and interactive
relationship between state and citizen, diffused across a much wider
and continual range of activities. To be capable of responding and
adapting across our complex, mass-scale societies, governments need
more than strategic brilliance and sophisticated networking. They
must also rely on new methods of deliberation and legitimation, both
to draw on the ideas and innovations generated by citizens, and to
make new priorities, tools and responsibilities acceptable.
In both these areas, innovation and adaptation in governance are lagging
behind the development of high-level strategic policy analysis which
draws rapidly from experience elsewhere. Without them, the emerging
global commons which Mulgan describes risks becoming the preserve
of an articulate and professional elite, which includes the most able
policy-makers and the best think-tanks, but is constrained by the
realities of institutional power and cut off from some of the most
significant innovative potential elsewhere.
While in many ways there have never been better conditions or incentives
for knowledge exchange and policy transfer, several factors remain
in todays policy environment which act as serious and damaging
constraints to the free flow of learning.
Governance as conceptual system
In the 20th century, the organisation of the state reflected the struggle
between competing ideologies. The triumph of liberal capitalism was
also a victory for the free and creative flow of ideas driven
as it is by openness, competition and exchange. The competing theories
of state and market were theories of knowledge as well as of power.
The logic of Friedrich von Hayek, which has largely won out in todays
world, is that when ideas are traded and information distributed across
systems of exchange, choice and efficiency are increased.
As Anthony Barnett points out in his introduction to the debate, Mulgans
synthesis reflects the idea that good government is a good in itself;
it does not have to justify itself purely by copying market mechanisms
in its attempt to coordinate large scale activity. But the assumptions
underpinning the shape of the modern state still need to be questioned,
because they influence the possibilities that can be considered as
policy options.
These assumptions are bound up in the ideal of neutral, dispassionate
analysis of policy choices and a cost-benefit approach
to their selection. This model is central to the design of European
bureaucracies and parliamentary systems, and its influence spread
across the world through immigration and empire in the 19th and 20th
centuries.
The legacy of this spread is a machinery of government which, at its
administrative core, is remarkably similar from Norway to Australia,
Japan to Canada, Greece to South Africa.
The core of the approach is a form of reductionism: the idea that
any complex policy problem can be broken apart into manageable chunks
and dealt with through functional departments deploying generalised
administrative skills. As a result, policy-making processes are supposed
to select the methods most appropriate to their specific objectives
and then implement them according to mechanistic principles, preserving
the principle of vertical accountability through which
every penny or cent of public expenditure can be traced from its eventual
destination; whether unemployment benefit, school voucher or cruise
missile, each can be linked back up a chain of command to the policy
choice which validated it.
This approach is designed to encourage efficiency (because it focused
public administration on achieving clear-cut, manageable objectives)
and transparency (because it can always be established whose responsibility
it is to deliver a particular policy outcome). But as many people
realise, the reality is far messier.
The people and societies which governments are trying to act on are
more interconnected and less likely to divide their problems and needs
up into neat functional units. Poor health may impact on housing need
and labour market participation, as well as the need for medical treatment.
Changes to budgeting rules for the sake of fiscal stability produce
direct consequences for domestic saving, unemployment levels, and
patterns of population mobility. Low inflation and interest rates
change consumption behaviour and the relative value of housing.
Over the last generation especially, societies have become more interconnected,
as globalisation and communications have made the movement of ideas,
people, money and culture faster and cheaper. As a result, governments
have to learn faster. And as Mulgan says, in a less ideological age,
the tendency for governments (or at least their strategic centres)
to operate like magpies, picking up ideas from all over and implementing
them one by one, becomes more pronounced.
This is one way to deal with a more diverse, possibly more complex
environment, when the demands of some citizens and interest groups
are more vociferous and the pressure of events and always-on media
is relentless. In other words, the factors which helped bring about
the victory of the liberal state have also increased the pressure
on it. Better and faster learning is one response.
As an organisational innovation, the Strategy Unit itself is a reaction
to the deficiency of this approach. It addresses complex, interconnected
and long term policy challenges through a cross-functional, team-based
approach to policy diagnosis, futures thinking and strategy. In the
process it is helping to pioneer a different mode of policy-making
which is increasingly echoed and imitated in other parts of the world.
But if the focus is too strongly on strategic learning from the centre,
good government in the 21st century will not achieve its full potential.
This is because responsiveness to the full range of citizen need is
not possible only by reprogramming the machinery of government at
policy level.
Implementation: from efficiency to responsiveness
Two examples illustrate this basic point.
The first is the management of people flow. Refugees and asylum-seekers
present a logistical nightmare to western governments. Not only do
governance systems have to meet, identify, and validate the identity
of individuals arriving unpredictably at national borders, but they
then have to be provided with a minimum of social support, have their
cases and appeals processed, be housed and have their movement, work
and access to social security regulated.
In this environment, national systems are caught between the growing
demand for immigration to be controlled and managed, the growing perception
of security risk from people flow, and the need to respect migrants
human rights and dignity.
There are many potential policy options currently in play, not least
those presented by Demos and openDemocracy in our joint People Flow
project. But no lasting policy solution will work that does not spread
the capacity to learn and adapt across implementation structures as
well as policy processes. Immigration officers and police must learn
how to identify and assess risk in new ways, and communicate with
other agencies more effectively. Local authorities need to find ways
of allocating housing and language support more effectively. Employment
agencies need to match new skills and income needs with local vacancies.
The point is that overarching principles and policy categories for
all these things may well need to be adjusted in the light of success
elsewhere, but the capacity of the implementation system to learn
for itself and from its own experience is just as vital to good governance.
Such learning capacity is not possible if all the different elements
of an implementation plan are simply understood as following rules
or instructions which are determined higher up the policy chain.
The second example is that of child welfare. Across many different
countries, concern about child abuse and neglect has risen with the
influence of high-profile media abduction cases and declining social
trust. Social exclusion has concentrated the risks of neglect, underdevelopment,
some kinds of abuse and even malnutrition among very specific groups
of children.
In theory, the growth of a target-based culture of accountability
should have made governance regimes less tolerant of negative outcomes
for children. But as many systems have found, designing structures
and rules which compel social workers or others to follow formal routines
and procedures with respect to children at risk does not automatically
improve outcomes or prevent system failure.
In fact, outcomes for children in specific local areas are strongly
influenced by the degree of trust, communication and informal coordination
between different agencies and communities themselves. The likelihood
of improving family circumstances or negotiating better solutions
for children is increased by increasing the ability of schools, families,
social services, health providers and so on to adapt in response to
specific circumstances, not necessarily to work more efficiently or
predictably according to a set of instructions.
The conclusion is clear: governance as learning must be
distributed very widely across those with responsibility for implementation
if it is going to sustain better outcomes for all.
Learning how to innovate
To be fair, several of the policy ideas that Geoff Mulgan cites as
having spread through learning are for systems which improve implementation,
such as restorative justice. But the change is usually not just greater
efficiency in processing a standard function, but also a shift in
peoples expectations of how to respond to a problem like youth
offending.
Across the core areas of government policy, from health and education
to regulation and tax administration, good government has to find
ways of providing goods and services which are more differentiated
to peoples own personal circumstances. Responsiveness to this
diversity has to be built into the administration of government services,
as well to the goals of policy.
This requires the development of implementation strategies which can
be continuously adjusted and adapted in the light of consistent feedback.
The examples I have used come from social policy, but the challenges
apply equally to other fields, such as improving productivity in small
firms, or regulating complex patterns of financial service provision.
Making more of our newfound ability to compare, contrast and borrow
from others therefore depends on getting organisations at ground level
to absorb and adapt ideas. This is an area where the British government
like most others is still struggling. It is true that
professions and other interest groups are often resistant to innovation
and threats to their specialist knowledge and status. But governments
do not have enough of the answers, or sufficient control to direct
their implementation everywhere, for practitioners to be overridden
or pushed aside in every case.
Policy-makers must learn how to foster innovation from within, as
well as competition and inspiration from without, and to create a
climate in which public service practitioners can be engaged in the
search for new ideas as anybody else. At Demos we have found that
more and more of our work involves partnership with practitioner and
delivery organisations, which tests out new approaches by applying
them in practice and developing strategies for learning from the results,
building networks for the exchange of ideas and experience which can
enhance this adaptive capacity. What is interesting is that a growing
range of collaboration with policy-makers in other countries on high-level
issues is informed and enriched by a base of direct, localised organisational
learning experience.
Democracy: from occasional choice to continuous input
The implication of all this is that governments must find out what
works through higher levels of experimentation, including simple trial
and error. And this is only likely to be politically possible when
the wider culture of debate is both more understanding and more forgiving
of specific failures. For this reason alone, a much broader and creative
engagement of citizens is essential in what is happening around them
and how it can be organised.
The critical shift, which will never be achieved only through smarter
policy-making, is to find ways of involving citizens not just in understanding
the problems and solutions, but also in contributing to them through
their everyday choices and behaviours. A system of governance in which
ideas travel faster through lateral networks of exchange has to be
a system in which public institutions harness the creative power
of citizens to generate detailed solutions. This is where network-based
methods for encouraging debate and deliberation intertwine with more
distributed organisational structures for service delivery.
There are some well-known examples of how participatory processes
can be used to generate better, and more legitimate policy decisions,
such as the budget-setting process used in the Brazilian city of Porto
Alegre, which combines neighbourhood forums and city-wide plenary
debates with detailed technical analysis and costing procedures to
combine the input of residents on what local priorities should be
with a sophisticated approach to resource allocation and fiscal discipline.
Elsewhere, experimentation with online consultation and deliberative
juries has also produced promising results in changing both the outcomes
and the public perception of difficult policy questions such as hospital
closures or housing management.
But the real, broader challenge is to define a form of distributed
democracy in which peoples own direct participation in
producing public goods like health, education and community safety
is expressed through the way that they deal with local institutions
and help create local public value, as well as the attention and voice
that they give to bigger and more abstract issues.
In all these cases, the very meaning of democracy starts to shift:
from choosing between simplified alternative programmes of policy
commitments to a more continuous exchange of ideas and
experience, and a public weighing of the costs and risks of alternative
options.
But this change has to be accompanied by the growth of new capabilities
among governance institutions. These need to communicate through peer-to-peer
networks and with diverse groups of citizens, to incorporate detailed
feedback information into everyday management, and pass lessons and
ideas back up the chains of command to inform high-level policy development.
The growth of a network-based culture of information and transparency
makes this kind of interaction between people and institutions possible.
It ought to make a wider range of choices realistic, by eroding the
invisible limitations imposed on us by our existing models of governance.
But as Geoff Mulgan notes, genuine learning and exchange of ideas
remains very much a face-to-face process, helped by the availability
of virtual connections and the ability to collect and analyse more
information, but made possible only by the existence of social cultures
and concrete organisational practices. Governance as learning will
be a reality not just when every strategic centre is networked, but
when the networks extend from the blue skies of long-term strategy
to the coalface of everyday experience.
Tom
Bentley is Director of DEMOS in the UK.
Copyright © Tom Bentley, 2003. Published by openDemocracy Ltd.
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